Dynamic Facial Expression Recognition Using A Bayesian Temporal Manifold Model
Caifeng Shan, Shaogang Gong, Peter William McOwan · 2006
In this paper, we propose a novel Bayesian approach to modelling tem-poral transitions of facial expressions represented in a manifold, with the aim of dynamical facial expression recognition in image sequences. A gener-alised expression manifold is derived by embedding image data into a low dimensional subspace using Supervised Locality Preserving Projections. A Bayesian temporal model is formulated to capture the dynamic facial ex-pression transition in the manifold. Our experimental results demonstrate the advantages gained from exploiting explicitly temporal information in ex-pression image sequences resulting in both superior recognition rates and improved robustness against static frame-based recognition methods. 1